1、Lessons Learned From Early Adopters of Finance AI2Finance transformation leaders(FTLs)pursuing AI are quickly realizing that AI adoption will take more time than anticipated.FTLs can read this research to learn from the experience of early adopters of finance AI,better plan their AI adoption strateg

2、y and ensure a more effective rollout.OverviewKey findings Despite being the first to use AI,early adopters of finance AI found that the speed to implement AI was generally slower than they initially anticipated.Talent and collaboration with enterprisewide AI efforts are key differentiators of early

3、 adopters of finance AI;early adopters more frequently had data science skills available to them and were more frequently involved in enterprise AI governance efforts.Early adopters of finance AI found that they did not have to set their ambitions and governance approach at the onset of their AI ini

4、tiatives.Instead,they were able to figure out those elements of their AI strategy as they experimented with the technology.The evaluation of ROI for AI remains a challenge,even for early adopters of finance AI.3Data insightsOver the last year,finance has made significant progress in AI adoption.The

5、percentage of finance functions using AI(i.e.,with ongoing AI pilots,AI in production or AI being used at scale)has gone up,from 37%in 2023 to 58%in 2024.This jump over the course of just one year is remarkable.In 2023,finance was a laggard in AI adoption compared to other administrative functions l

6、ike HR,legal,real estate and procurement.But in 2024,finance has closed that gap and has done so due to significant efforts and investments from across the function.Indeed,the increase in AI adoption has been hard-earned.Almost half of finance leaders currently using AI report that their AI adoption